code: def test_conf_mat_missing_values_with_classes(mock_run):
      _ = mock_run(settings={"mode": "offline"})
      class_names = ["Cat", "Dog", "Bird"]
      y_true = [1, 2, 1, 2]
      y_pred = [2, 1, 1, 2]
      conf_mat = confusion_matrix(
          preds=y_pred,
          y_true=y_true,
          class_names=class_names,
          title="New title",
      )
      assert conf_mat.table.data[0] == ["Cat", "Cat", 0]
      assert conf_mat.table.data[1] == ["Cat", "Dog", 0]
      assert conf_mat.table.data[2] == ["Cat", "Bird", 0]
  
      assert conf_mat.table.data[3] == ["Dog", "Cat", 0]
      assert conf_mat.table.data[4] == ["Dog", "Dog", 1]
      assert conf_mat.table.data[5] == ["Dog", "Bird", 1]
  
      assert conf_mat.table.data[6] == ["Bird", "Cat", 0]
      assert conf_mat.table.data[7] == ["Bird", "Dog", 1]
      assert conf_mat.table.data[8] == ["Bird", "Bird", 1]
  
file_path: wandb/tests/pytest_tests/unit_tests/test_plot.py
imports: import pytest
  from sklearn.naive_bayes import MultinomialNB
  from wandb.plot import confusion_matrix, line_series, pr_curve, roc_curve
label_desc: Use image node_id 5 for calling a global function with example usage: test_conf_mat_missing_values_with_classes(mock_run) without return types